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Black spot disease, caused by Alternaria alternata , is one of the most destructive diseases of jujube worldwide. To better understand the resistance mechanisms of jujube to A. alternata infection, two different cultivars, Zizyphus jujuba Mill. var. Junzao (susceptible) and Zizyphus jujuba Mill. var. Huizao (resistant) were tested. In this study, we identified 2235 differentially expressed genes (DEGs) in the disease-resistant cultivar and 4958 in the susceptible cultivar. Most were associated with plant phytohormone synthesis and signal transduction, flavonoid synthesis, and glutathione metabolism. The expression of six DEGs associated with disease resistance was detected by real-time quantitative polymerase chain reaction (RT-qPCR), consistent with the results of Illumina transcriptome sequencing. Moreover, the distinct expression level of the six DEGs in Jun jujube and Hui jujube, verified that these are defense response factors. The present study identified several candidate resistance genes and signal transduction pathways that may contribute to black spot disease resistance in jujube, which will assist the investigation of resistance mechanisms in the response of jujube to A. alternata infection. • Two different disease-resistant jujube cultivars to A. alternata were tested. • Transcriptomics analysis was used for the screening of resistance DEGs. • Most of DEGs were associated with plant phytohormone synthesis, etc. • Six DEGs associated with disease resistance were verified by RT-qPCR. [ABSTRACT FROM AUTHOR]

Phosphate may affect the behavior of metal(loid)s in environments, so the interaction of Sb(III) with FeS affected by phosphate was investigated in this study. Sb(III) was reacted with synthesized FeS in solution at pH 5.5, 7.0, and 9.0 with and without the addition of phosphate. The concentrations of Fe(II), Sb(III), and phosphate in the solution were monitored, and the solid phases were examined by XRD, TEM, and XPS. For the interaction of Sb(III) with FeS in the absence of phosphate, the formation of Sb 2 S 3 was very important at pH 5.5 and 7.0, whereas Sb(III) adsorption was the dominant process at pH 9.0. The interaction of Sb(III) with FeS could be significantly affected by phosphate, and this impact was dependent of pH and phosphate concentration. At pH 5.5 and 7.0, the effect of phosphate varied markedly with increasing phosphate concentration. Low phosphate loadings (9.5 and 19 mg/L) had a negligible effect on the mobility of Sb(III), while high phosphate loadings (95 and 475 mg/L) notably enhanced the uptake of Sb(III) by FeS. In the case of high phosphate loadings, Fe 3 (PO 4) 2 ‧8H 2 O was formed and resulted in the dissolution of FeS, which was favorable for the formation of Sb 2 S 3 and consequently the uptake of Sb(III). In the experiments at pH 9.0, the addition of phosphate only resulted in minor desorption of Sb(III) because FeS was very stable and consequently both Fe 3 (PO 4) 2 ‧8H 2 O and Sb 2 S 3 were unlikely to be formed. The results of this work may help to better understand the effect of phosphate on the behavior of Sb in some anoxic environments where FeS is present. [Display omitted] • The interaction of Sb(III) with FeS was significantly affected by PO 4 3-. • The effect of PO 4 3− was dependent on pH and PO 4 3− concentration. • At pH 5.5 and 7.0, high PO 4 3− loadings resulted in the formation of Fe 3 (PO 4) 2 ‧8H 2 O. • Fe 3 (PO 4) 2 ‧8H 2 O formation enhanced the formation of Sb 2 S 3 and the uptake of Sb(III). [ABSTRACT FROM AUTHOR]

Abstract: Without template, three-dimensional nanowall ZnO films were synthesized in an atmospheric pressure chemical vapor deposition (APCVD) system by adjusting zinc species concentration. In the high ordered film, the vertical nanosheets were assembled along three directions angled approximately 120°. The extremely strong ZnO (0002) peaks in X-ray diffraction patterns testified the preferred (0001) orientation and high crystalline quality of the films. The low transmittances of nanowall films were attributed to the strong inner reflection and scattering. These results show that the simplified APCVD method is potential in synthesizing uniform nanowall ZnO films. [Copyright &y& Elsevier]

Background: Chinese Bama Yao Autonomous County is a well-known longevity region in the world. In the past 30 years, population and genome studies were undertaken to investigate the secret of longevity and showed that longevity is the result of a combination of multiple factors, such as genetic, environmental and other causes. In this study, characteristics of the blood plasma proteomic and autoantibody profiles of people from Bama longevity family were investigated. Methods: Sixty-six plasma donors from Chinese Bama longevity area were recruited in this study. Thirty-three offsprings of longevous families were selected as case studies (Longevous group) and 33 ABO (blood type), age, and gender-matched subjects from non-longevous families were selected as controls (Normal group). Each group contains 3 biological replicates. Tandem mass tag-based proteomic technique was used to investigate the differentially expressed plasma proteins between the two groups. The auto-reactive IgG antibody profiles of the 3 pooled samples in each group were revealed by human proteome microarrays with 17,000 recombinant human proteins. Results: Firstly, 525 plasma proteins were quantified and 12 proteins were discovered differentially expressed between the two groups. Secondly, more than 500 proteins were recognized by plasma antibodies, 14 proteins ware differentially reacted with the autoantibodies in the two groups. Bioinformatics analysis showed some of the differential proteins and targeted autoantigens were involved in cancer, cardiovascular disease and immunity. Conclusions: Proteomic and autoantibody profiles varied between the offspring of longevous and normal families which are from the same area and shared the same environmental factors. The identified differences were reported to be involved in several physiological and pathological pathways. The identified proteins will contribute to a better understanding of the proteomic characteristics of people from Bama longevous area and a revelation of the molecular mechanisms of longevity. [ABSTRACT FROM AUTHOR]

Cognitive diagnosis is a crucial element of intelligent education that aims to assess the proficiency of specific skills or traits in students at a refined level and provide insights into their strengths and weaknesses for personalized learning. Researchers have developed numerous cognitive diagnostic models. However, previous studies indicate that diagnostic accuracy can be significantly influenced by the appropriateness of the model and the sample size. Thus, designing a general model that can adapt to different assumptions and sample sizes remains a considerable challenge. Artificial neural networks have been proposed as a promising approach in some studies. In this paper, we propose a cognitive diagnosis model of a neural network constrained by a Q-matrix and named QNN. Specifically, we employ the Q-matrix to determine the connections between neurons and the width and depth of the neural network. Moreover, to reduce the human effort in the training algorithm, we designed a self-organizing map-based cognitive diagnosis training framework called SOM-NN, which enables the QNN to be trained unsupervised. Extensive experimental results on simulated and real datasets demonstrate that our approaches are effective in both accuracy and interpretability. Notably, under unsupervised conditions, our approach has significant advantages on small sample datasets with high levels of guessing and slipping, especially on the pattern-wise agreement rates. This work bridges the gap between psychometrics and machine learning and provides a realistic and implementable reference solution for classroom instructional assessment and the cold start of personalized and adaptive assessment systems., (© 2024. The Psychonomic Society, Inc.)

Abnormal plasma uric acid (UA) levels, the lipid profile, and plasma proteins in blood are associated with a range of adverse health outcomes. This multicenter, prospective cohort study aimed to determine the possible effects of multiple apheresis plasma donations on plasma UA levels, the lipid profile, and major proteins in plasma donors. Participants were enrolled from 1 April 2021 to 31 August 2022. When their plasma UA (men: >420 µmol/L, women: >360 µmol/L) and/or lipid levels (total cholesterol [TC]: ≥6.2 mmol/L, triglycerides [TGs]: ≥2.3 mmol/L, low-density lipoprotein cholesterol: ≥4.1 mmol/L, or high-density lipoprotein cholesterol [HDL-C]: <1.0 mmol/L) were abnormal at their first plasma donation, the enrolled participants were followed up until they had completed 10 plasma donations. A total of 11485 participants were enrolled, of whom 1861 met the inclusion criteria. During the study period, 320 donors completed 10 plasma donations. None of the participants took any corrective medicine for their abnormal index. The measured parameters were significantly different from the first to the tenth plasma donations (donors with asymptomatic hyperuricemia: UA, P < 0.001; donors with asymptomatic hyperlipidemia: HDL-C, P < 0.001; TC, P = 0.025; TGs, P < 0.001; apolipoprotein B, P = 0.025; all of the plasma donors, immunoglobulin G, P < 0.001). The levels of HDL-C, TC, and apolipoprotein B were increased, and the levels of UA, TGs, and immunoglobulin G were decreased over this time. However, immunoglobulin G levels were still in the normal range. Moreover, the changes in these parameters were closely associated with the frequency of plasma donation during the study period. Repeated apheresis plasma donations can reduce plasma UA and TG levels and increase HDL-C levels; and further evaluation of the clinical significance with a larger sample size is required., Competing Interests: Conflict of interest statement The authors declare no conflict of interest., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Healthy, nutritious, and delicious mulberry wine is loved by everyone, but there is no specific yeast for mulberry wine. To screen for yeasts with low-yield higher alcohols for the fermentation of mulberry wine, we tested five commonly used commercial yeasts available on the market to ferment mulberry wine. All five yeasts were able to meet the requirements in terms of yeast fermentation capacity, speed, and physical and chemical markers of mulberry wine. The national standards were met by the fermentation requirements and the fermented mulberry wine. We identified yeast DV10 as a yeast with low-yield higher alcohols suitable for mulberry wine fermentation. The total higher alcohol content in fermented mulberry wine was 298 mg/L, which was 41.9% lower than that of fermented mulberry wine with yeast EC118. The contents of 17 free amino acids and five sugars in mulberry juice and five yeast-fermented mulberry wines were tested. The results showed that the higher the amino acid and sugar content in yeast-fermented mulberry wine, the higher the content of higher alcohols produced by fermentation. A correlation analysis performed on each higher alcohol produced when yeast DV10 fermented the mulberry wine indicated decreased sugar and related amino acids. The findings demonstrated a substantial negative correlation among the levels of increased alcohol, decreased sugar, and matching amino acid content. Considering the correlation values among increased alcohol, decreased sugar, and related amino acids, the very slight difference suggests that both sugar anabolism and amino acid catabolism pathways have an equivalent impact on the synthesis of higher alcohols during the fermentation of mulberry wine. These results provide a theoretical basis for reducing the content of higher alcohols in mulberry wines, given the history and foundation for producing mulberry wine.

Raisins, known for their delicious taste and high nutritional value, are among the most widely consumed dried fruits globally. The natural waxy layer on the surface of grapes impedes water migration, making pretreatment necessary before drying. This study evaluated the effects of various pretreatment methods on the nutritional and functional quality of seedless purple raisins. By using non-pretreated dry seedless purple raisins as a control, the impact of physical and chemical pretreatment methods on the nutritional and functional qualities of seedless purple raisins was assessed through the analysis of nutrient content, phenolic compounds, and antioxidant activity. Our results demonstrate that physical pretreatment significantly increases the levels of vitamin C, fructose, glucose, total acid, total phenolics, total flavonoids, total anthocyanins, and antioxidant activity compared to chemical pretreatment and the control group. The correlation analysis revealed that phenolic substances were closely linked to antioxidant capacity. Additionally, phenolic compounds, including resveratrol, ferulic acid, chlorogenic acid, ethyl coumarate, and cinnamic acid, were more abundant following physical pretreatment. The OPLS-DA model effectively differentiated the three groups of processed samples, showing that different pretreatments significantly affect the nutritional and functional quality of seedless purple raisins. These findings suggest that physical pretreatment offers considerable potential for improving the drying quality of seedless purple raisins.

The microbes on fresh processing tomatoes correlate closely with diseases, preservation, and quality control. Investigation of the microbial communities on processing tomatoes from different production regions may help define microbial specificity, inform disease prevention methods, and improve quality. In this study, surface microbes on processing tomatoes from 10 samples in two primary production areas of southern and northern Xinjiang were investigated by sequencing fungal internal transcribed spacer and bacterial 16S rRNA hypervariable sequences. A total of 133 different fungal and bacterial taxonomies were obtained from processing tomatoes in the two regions, of which 63 genera were predominant. Bacterial and fungal communities differed significantly between southern and northern Xinjiang, and fungal diversity was higher in southern Xinjiang. Alternaria and Cladosporium on processing tomatoes in southern Xinjiang were associated with plant pathogenic risk. The plant pathogenic fungi of processing tomatoes in northern Xinjiang were more abundant in Alternaria and Fusarium . The abundance of Alternaria on processing tomatoes was higher in four regions of northern Xinjiang, indicating that there is a greater risk of plant pathogenicity in these areas. Processing tomatoes in northern and southern Xinjiang contained bacterial genera identified as gut microbes, such as Pantoea , Erwinia , Enterobacter , Enterococcus , and Serratia , indicating the potential risk of contamination of processing tomatoes with foodborne pathogens. This study highlighted the microbial specificity of processing tomatoes in two tomato production regions, providing a basis for further investigation and screening for foodborne pathogenic microorganisms.

Alternaria spp. and its toxins are the main contaminants in processing tomato. Based on our earlier research, the current study looked into the anti-fungal capacity of crude lipopeptides from B. amyloliquefaciens XJ-BV2007 against A. alternata . We found that the crude lipopeptides significantly inhibited A. alternata growth and reduced tomato black spot disease incidence. SEM analysis found that the crude lipopeptides could change the morphology of mycelium and spores of A. alternata . Four main Alternaria toxins were detected using UPLC-MS/MS, and the findings demonstrated that the crude lipopeptides could lessen the accumulation of Alternaria toxins in vivo and in vitro. Meanwhile, under the stress of crude lipopeptides, the expression of critical biosynthetic genes responsible for TeA, AOH, and AME was substantially down-regulated. The inhibitory mechanism of the crude lipopeptides was demonstrated to be the disruption of the mycelial structure of A. alternata , as well as the integrity and permeability of the membrane of A. alternata sporocytes. Taken together, crude lipopeptides extracted from B. amyloliquefaciens XJ-BV2007 are an effective biological agent for controlling tomato black spot disease and Alternaria toxins contamination.

As the most important melon cultivar grown in the north-western provinces of China, Hami melon ( Cucumis melo ) produces large edible fruits that serve as an important dietary component in the world. In general, as a climacteric plant, melon harvested at 60% maturity results in a product with bad quality, while the highest-quality product can be guaranteed when harvesting at 90% maturity. In order to clarify the genetic basis of their distinct profiles of metabolite accumulation, we performed systematic transcriptome analyses between 60% and 90% maturity melons. A total of 36 samples were sequenced and over 1.7 billion reads were generated. Differentially expressed genes in 60% and 90% maturity melons were detected. Hundreds of these genes were functionally enriched in the sucrose and citric acid accumulation process of C. melo . We also detected a number of distinct splicing events between 60% and 90% maturity melons. Many genes associated with sucrose and citric acid accumulation displayed as differentially expressed or differentially spliced between different degrees of maturity of Hami melons, including CmCIN2 , CmSPS2 , CmBGAL3 , and CmSPS2 . These results demonstrate that the phenotype pattern differences between 60% and 90% maturity melons may be largely resulted from the significant transcriptome regulation.

Diabetes is a major global public health problem with high incidence and case fatality rates. Traditional Chinese medicine (TCM) is used to help manage Type 2 Diabetes Mellitus (T2DM) and has steadily gained international acceptance. Despite being generally accepted in daily practice, the TCM methods and hypotheses for understanding diseases lack applicability in the current scientific characterization systems. To date, there is no systematic evaluation system for TCM in preventing and treating T2DM. Metabonomics is a powerful tool to predict the level of metabolites in vivo, reveal the potential mechanism, and diagnose the physiological state of patients in time to guide the follow-up intervention of T2DM. Notably, metabolomics is also effective in promoting TCM modernization and advancement in personalized medicine. This review provides updated knowledge on applying metabolomics to TCM syndrome differentiation, diagnosis, biomarker discovery, and treatment of T2DM by TCM. Its application in diabetic complications is discussed. The combination of multi-omics and microbiome to fully elucidate the use of TCM to treat T2DM is further envisioned., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Li et al.)

Intravenous immunoglobulin (IVIG) is a first-line drug prepared from human plasma for the treatment of autoimmune diseases (AIDs), especially immune thrombocytopenia (ITP). Significant differences exist in protein types and expression levels between male and female plasma, and the prevalence of autoimmune diseases varies between sexes. The present study seeks to explore potential variations in IVIG sourced from distinct sex-specific plasma (DSP-IVIG), including IVIG sourced from female plasma (F-IVIG), IVIG sourced from male plasma (M-IVIG), and IVIG sourced from a blend of male and female plasma (Mix-IVIG). To address this question, we used an ITP mouse model and a monocyte-macrophage inflammation model treated with DSP IVIG. The analysis of proteomics in mice suggested that the pathogenesis and treatment of ITP may involve FcγRs mediated phagocytosis, apoptosis, Th17, cytokines, chemokines, and more. Key indicators, including the mouse spleen index, CD16 + macrophages, M1, M2, IL-6, IL-27, and IL-13, all indicated that the efficacy in improving ITP was highest for M-IVIG. Subsequent cell experiments revealed that M-IVIG exhibited a more potent ability to inhibit monocyte phagocytosis. It induced more necrotic M2 cells and fewer viable M2, resulting in weaker M2 phagocytosis. M-IVIG also demonstrated superiority in the downregulation of surface makers CD36, CD68, and CD16 on M1 macrophages, a weaker capacity to activate complement, and a stronger binding ability to FcγRs on the THP-1 surface. In summary, DSP-IVIG effectively mitigated inflammation in ITP mice and monocytes and macrophages. However, M-IVIG exhibited advantages in improving the spleen index, regulating the number and typing of M1 and M2 macrophages, and inhibiting macrophage-mediated inflammation compared to F-IVIG and Mix-IVIG.

Autophagy is a primary mechanism for maintaining cellular homeostasis. The synergistic actions of autophagy-related (ATG) proteins strictly regulate the whole autophagic process. Therefore, accurate identification of ATGs is a first and critical step to reveal the molecular mechanism underlying the regulation of autophagy. Current computational methods can predict ATGs from primary protein sequences, but owing to the limitations of algorithms, significant room for improvement still exists. In this research, we propose EnsembleDL-ATG, an ensemble deep learning framework that aggregates multiple deep learning models to predict ATGs from protein sequence and evolutionary information. We first evaluated the performance of individual networks for various feature descriptors to identify the most promising models. Then, we explored all possible combinations of independent models to select the most effective ensemble architecture. The final framework was built and maintained by an organization of four different deep learning models. Experimental results show that our proposed method achieves a prediction accuracy of 94.5 % and MCC of 0.890, which are nearly 4 % and 0.08 higher than ATGPred-FL, respectively. Overall, EnsembleDL-ATG is the first ATG machine learning predictor based on ensemble deep learning. The benchmark data and code utilized in this study can be accessed for free at https://github.com/jingry/autoBioSeqpy/tree/2.0/examples/EnsembleDL-ATG., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Objective: Using PSG-guided acute selective REM/SWS sleep deprivation in volunteers, this study examined the effects of sleep deprivation on the cardiovascular and autonomic nervous systems, as well as the relationship between cardiac neuromodulation homeostasis and cardiovascular disease., Methods: An experiment was conducted using 30 healthy volunteers (male : female = 1 : 1, aged 26.33 ± 4.5 years) divided into groups for sleep deprivation of SWS and REM sleep, and then, each group was crossed over for normal sleep (2 days) and repeated sleep deprivation (1 day, 3 times). During the study period, PSG and ELECTRO ECG monitoring were conducted, and five-minute frequency domain parameters and blood pressure values were measured before and after sleep deprivation., Results: Changes in VLF, LFnu, LF/HF, HF, and HFnu after SWS sleep deprivation were statistically significant ( P < 0.05), but not LF ( P = 0.063). Changes in VLF, LF, HF, LF/HF, LFnu, and HFnu after REM sleep deprivation were not statistically significant ( P > 0.05)., Conclusions: An increase in sympathetic nerve activity results from sleep deprivation and sudden awakening from SWS sleep is associated with a greater risk of cardiovascular disease., Competing Interests: It is claimed that none of the researchers have any conflicts of interest., (Copyright © 2023 YaHui Xu et al.)

Post-transcriptionally RNA modifications, also known as the epitranscriptome, play crucial roles in the regulation of gene expression during development. Recently, deep learning (DL) has been employed for RNA modification site prediction and has shown promising results. However, due to the lack of relevant studies, it is unclear which DL architecture is best suited for some pyrimidine modifications, such as 5-methyluridine (m 5 U). To fill this knowledge gap, we first performed a comparative evaluation of various commonly used DL models for epigenetic studies with the help of autoBioSeqpy. We identified optimal architectural variations for m 5 U site classification, optimizing the layer depth and neuron width. Second, we used this knowledge to develop Deepm5U, an improved convolutional-recurrent neural network that accurately predicts m 5 U sites from RNA sequences. We successfully applied Deepm5U to transcriptomewide m 5 U profiling data across different sequencing technologies and cell types. Third, we showed that the techniques for interpreting deep neural networks, including LayerUMAP and DeepSHAP, can provide important insights into the internal operation and behavior of models. Overall, we offered practical guidance for the development, benchmark, and analysis of deep learning models when designing new algorithms for RNA modifications., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yu, Zhang, Xue, Liu, Jing and Luo.)

Amorphous oxide semiconductor thin-film transistors (AOS TFTs) are ever-increasingly utilized in displays. However, to bring high mobility and excellent stability together is a daunting challenge. Here, the carrier transport/relaxation bilayer stacked AOS TFTs are investigated to solve the mobility-stability conflict. The charge transport layer (CTL) is made of amorphous In-rich InSnZnO, which favors big average effective coordination number for all cations and more edge-shared structures for better charge transport. Praseodymium-doped InSnZnO is used as the charge relaxation layer (CRL), which substantially shortens the photoelectron lifetime as revealed by femtosecond transient absorption spectroscopy. The CTL and CRL with the thickness suitable for industrial production respectively afford minute potential barrier fluctuation for charge transport and fast relaxation for photo-generated carriers, resulting in transistors with an ultrahigh mobility (75.5 cm 2 V -1 s -1 ) and small negative-bias-illumination-stress/positive-bias-temperature-stress voltage shifts (-1.64/0.76 V). The design concept provides a promising route to address the mobility-stability conflict for high-end displays., (© 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Background: The efficacy and safety of osimertinib combined with bevacizumab in non-small cell lung cancer (NSCLC) patients with brain metastasis harboring epidermal growth factor receptor (EGFR) mutations have not been fully studied., Methods: Treatment-naïve NSCLC patients with brain metastasis harboring EGFR-activating mutations were treated with osimertinib 80 mg oral daily and bevacizumab 15 mg/kg intravenously on day 1, repeated every 21 days, until disease progression, intolerable toxicity, or death. The primary endpoint was the median progression-free survival (mPFS), and the secondary endpoints were the median overall survival (mOS), response rates, and toxicities. This study has been registered in ClinicalTrials.gov (NCT05104281) and is ongoing., Results: A total of 52 Chinese patients were enrolled, of whom 17 harbored EGFR 19 del and 35 harbored EGFR L858R mutation. The objective response rate (ORR) was 75.0% and the disease control rate (DCR) was 96.2%; the mPFS was 17.0 months (95% CI: 11.46-22.54), while the mOS was not reached. The mPFS was 20.0 months (95% CI: 14.56-25.44) and was 17.0 months (95% CI: 13.28-20.72) for patients harboring EGFR 19 del and EGFR L858R mutation (p = 0.844), respectively. The intracranial ORR was 82.7%, and the intracranial mPFS was 22.0 months (95% CI: 2.92-41.08).The main adverse events were mild-to-moderate hand-foot syndrome, diarrhea, hypertension, and proteinuria. Three patients developed grade III proteinuria, while five patients developed grade III hypertension; they permanently discontinued bevacizumab treatment., Conclusions: Osimertinib combined with bevacizumab shows promising results in EGFR-mutated NSCLC patients with brain metastasis, and the side effects are tolerable., (© 2023 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.)

Patulin (PAT) is a toxic secondary metabolite produced by Aspergillus sp. and Penicillium sp., which acts as a contaminant of most apples and their products. The internationally recognized HACCP system is selected as the theoretical basis to more effectively reduce the PAT in apple juice concentrate (AJC). Through field investigation of apple juice concentrate (AJC) production enterprises, we collected 117 samples from 13 steps of AJC production, including whole apple, apple pulp, and apple juice. PAT contents were analyzed via high-performance liquid chromatography (HPLC) and compared with samples from the different production processes. The result demonstrated that the PAT content was significantly ( p < 0.05) influenced by five processes, receipt of raw apples, sorting of raw apples, adsorption step, pasteurization, and aseptic filling. These processes were determined as the CCPs. Monitoring systems for maintaining CCPs within acceptable limits were established, and corrective actions were proposed in case a CCP was surpassed. Based on the above-identified CCPs, critical limits, and control methods (corrective actions), a HACCP plan related to the production process of AJC was established. This study provided important guidance for juice manufacturers wishing to effectively control the PAT content in their products.

Background and Objectives: The adverse effects of plasma donation on the body has lowered the odds of donation. The aim of this study was to investigate the prevalence of abnormal serum calcium and total serum protein related to plasma donation, identify the influencing factors, and come up with suggestions to make plasma donation safer., Methods: Donors from 10 plasmapheresis centers in five provinces of China participated in this study. Serum samples were collected before donation. Serum calcium was measured by arsenazo III colorimetry, and the biuret method was used for total serum protein assay. An automatic biochemical analyzer was used to conduct serum calcium and total serum protein tests., Results: The mean serum calcium was 2.3 ± 0.15 mmol/L and total serum protein was 67.75 ± 6.02 g/L. The proportions of plasma donors whose serum calcium and total serum protein were lower than normal were 20.55% (815/3,966) and 27.99% (1,111/3,969), respectively. There were significant differences in mean serum calcium and total serum protein of plasma donors with different plasma donation frequencies, gender, age, regions, and body mass index (BMI), (all p  < 0.05). Logistic regression analysis revealed that donation frequencies, age, BMI and regions were significantly associated with a higher risk of low serum calcium level, and donation frequencies, gender, age and regions were significant determinants factors of odds of abnormal total serum protein., Conclusions: Donation frequencies, gender, age, regions, and BMI showed different effects on serum calcium and total serum protein. More attention should be paid to the age, donation frequency and region of plasma donors to reduce the probability of low serum calcium and low total serum protein., Competing Interests: Demei Dong and Yang Gao are employees of Beijing Tiantan Biological Products Co., LTD. Ding Yu is an employee of Chengdu Rongsheng Pharmaceuticals Co., LTD. The authors declare there are no competing interests., (©2022 Liu et al.)

Background: High blood glucose level is one of the main characteristics of diabetes mellitus. Based on previous studies, it is speculated longevity families may have certain advantages in blood glucose regulation. However, limited information on these items has been reported. The purpose of this study was to profile differences of plasma proteomics between longevity subjects (with normal fructosamine (FUN) level) and non-longevity area participants (with exceeding standard FUN level)., Methods: In this study, a TMT-based proteomics analysis was used to profile differences of plasma proteomics between longevity subjects (with normal FUN level) and non-longevity area participants (with exceeding standard FUN level). Results were validated by Luminex detection., Results: A total of 155 differentially expressed proteins (DEPs) were identified between these two groups. The DEPs related to blood glucose regulation were mainly involved in glycolysis/gluconeogenesis, pyruvate metabolism and propanoate metabolism, and most of the DEPs were contained in carbohydrate metabolism, PI3K-Akt pathway, glucagon signaling pathway and inflammatory response. Validation by Luminex detection confirmed that CD163 was down-regulated, and SPARC, PARK 7 and IGFBP-1 were up-regulated in longevity participants., Conclusions: This study not only highlighted carbohydrate metabolism, PI3K-Akt pathway, glucagon signaling pathway and inflammatory response may play important roles in blood glucose regulation, but also indicated that YWHAZ, YWHAB, YWHAG, YWHAE, CALM3, CRP, SAA2, PARK 7, IGFBP1 and VNN1 may serve as potential biomarkers for predicting abnormal blood glucose levels., (© 2022. The Author(s).)

Introduction: The top priority in drug development is to identify novel and effective drug targets. In vitro assays are frequently used for this purpose; however, traditional experimental approaches are insufficient for large-scale exploration of novel drug targets, as they are expensive, time-consuming and laborious. Therefore, computational methods have emerged in recent decades as an alternative to aid experimental drug discovery studies by developing sophisticated predictive models to estimate unknown drugs/compounds and their targets. The recent success of deep learning (DL) techniques in machine learning and artificial intelligence has further attracted a great deal of attention in the biomedicine field, including computational drug discovery., Objectives: This study focuses on the practical applications of deep learning algorithms for predicting druggable proteins and proposes a powerful predictor for fast and accurate identification of potential drug targets., Methods: Using a gold-standard dataset, we explored several typical protein features and different deep learning algorithms and evaluated their performance in a comprehensive way. We provide an overview of the entire experimental process, including protein features and descriptors, neural network architectures, libraries and toolkits for deep learning modelling, performance evaluation metrics, model interpretation and visualization., Results: Experimental results show that the hybrid model (architecture: CNN-RNN (BiLSTM) + DNN; feature: dictionary encoding + DC&#95;TC&#95;CTD) performed better than the other models on the benchmark dataset. This hybrid model was able to achieve 90.0% accuracy and 0.800 MCC on the test dataset and 84.8% and 0.703 on a nonredundant independent test dataset, which is comparable to those of existing methods., Conclusion: We developed the first deep learning-based classifier for fast and accurate identification of potential druggable proteins. We hope that this study will be helpful for future researchers who would like to use deep learning techniques to develop relevant predictive models., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Production and hosting by Elsevier B.V.)

Growth differentiation factor 11 (GDF11), belonging to the transforming factor-β superfamily, regulates anterior-posterior patterning and inhibits neurogenesis during embryonic development. However, recent studies recognized GDF11 as a rejuvenating (or anti-ageing) factor to reverse age-related cardiac hypertrophy, repair injured skeletal muscle, promote cognitive function, etc. The effects of GDF11 are contradictory and the mechanism of action is still not well clarified. The objective of the present study was to investigate effects of GDF11 on PC12 neural stem cells in vitro and to reveal the underlying mechanism. We systematically assessed the effects of GDF11 on the life activities of PC12 cells. GDF11 significantly suppressed cell proliferation and migration, promoted differentiation and apoptosis, and arrested cell cycle at G2/M phase. Both TMT-based proteomic analysis and phospho-antibody microarray revealed PI3K-Akt pathway was enriched when treated with GDF11. Inhibition of ALK5 or PI3K obviously attenuated the effects of GDF11 on PC12 neural stem cells, which exerted that GDF11 regulated neural stem cells through ALK5-dependent PI3K-Akt signaling pathway. In summary, these results demonstrated GDF11 could be a negative regulator for neurogenesis via ALK5 activating PI3K-Akt pathway when it directly acted on neural stem cells.

Senescence is the inevitable biological processes and is also considered as the biggest risk factor for the development of age - related diseases (ARDs) and geriatric syndrome (GS). Senescence is also known as inflammaging because it is characterized by persistent, long-term, low-grade inflammation named senescence-associated secretory phenotype (SASP). However, the mechanism for the persistence of inflammaging remains largely unclear. To explore the role of extracellular vesicles (EVs) in senescence/inflammaging, we established the cellular senescence model and performed TMT-based comparative quantitative proteomics and parallel reaction monitoring (PRM) to reveal the changes of EVs between young cells and senescent cells. A total of 3966 proteins were quantifiable, of which 132 were up-regulated, 144 were down-regulated, compared with the young cells. Subsequently, we chose 19 proteins involved in inflammation or proliferation to carry out PRM validation analysis. The result indicated that proteins promoting NF-κB signal pathway were up-regulated, and proteins promoting cell proliferation were down-regulated. The study provided a comprehensive altered proteomics profiles of EVs from senescent cells, and the result showed that EVs could serve as information carrier for further research on the pathogenesis and progression of senescence/inflammaging. SIGNIFICANCE: The mechanism of inflammaging occurrence and development has yet been clear. Therefore, this study attempts to provide an improved understanding of inflammaging from the perspective of EVs. The proteomics analysis revealed that the most changed proteins were connected to inflammation signaling pathways, cell growth and cell death, and PRM analysis results showed that proteins involved in NF-κB signal pathway and cell proliferation were more changed. The research systematically analyzed the profiles of proteins in senescence cell model, and the result indicated that further research should focus on the relationship between EVs and senescence/inflammaging., (Copyright © 2022 Elsevier B.V. All rights reserved.)

DNA N 4 -methylcytosine (4mC) is a pivotal epigenetic modification that plays an essential role in DNA replication, repair, expression and differentiation. To gain insight into the biological functions of 4mC, it is critical to identify their modification sites in the genomics. Recently, deep learning has become increasingly popular in recent years and frequently employed for the 4mC site identification. However, a systematic analysis of how to build predictive models using deep learning techniques is still lacking. In this work, we first summarized all existing deep learning-based predictors and systematically analyzed their models, features and datasets, etc. Then, using a typical standard dataset with three species ( A. thaliana , C. elegans , and D. melanogaster ), we assessed the contribution of different model architectures, encoding methods and the attention mechanism in establishing a deep learning-based model for the 4mC site prediction. After a series of optimizations, convolutional-recurrent neural network architecture using the one-hot encoding and attention mechanism achieved the best overall prediction performance. Extensive comparison experiments were conducted based on the same dataset. This work will be helpful for researchers who would like to build the 4mC prediction models using deep learning in the future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Yu, Zhang, Xue, Liu, Chen, Luo and Jing.)

A modified quick, easy, cheap, effective, rugged, and safe extraction procedure combined with ultra-performance liquid chromatographic separation and ion mobility quadrupole time-of-flight mass spectrometry was developed to determine the presence of 20 mycotoxins (i.e., Alternaria toxins, ochratoxin, patulin, aflatoxin and trichothecenes) in fruit samples from Xinjiang. A complete platform, including screening via an in-house library, confirmation and quantification using reference standards, was established, which provided accurate MS data and complete spectra containing the fragment ions for each analyte. To evaluate the performance of the developed method, satisfactory validation parameters, such as linearity (R 2  ≥ 0.9992), precision (RSDs ≤ 9.8%), recovery (81.2-99.2%), LOD (0.06-2.22 µg kg -1 ), and LOQ (0.2-7.39 µg kg -1 ), were obtained. The analysis of 130 fruit samples revealed nonnegligible contamination with mycotoxins; specifically, the highest levels of three Alternaria toxins were detected in jujube, wolfberries and raisins., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: As the most basic material, synthetic human Amyloid-β (1-42) (Aβ 42 ) peptide from different manufacturers have been widely used. Their aggregation ability is vital to the reliability, repeatability and comparability of studies on Aβ 42 physiology and pathology. However, it has not been evaluated and compared., Objective: To analyze the consistency of the aggregation ability of 5 commercially available Aβ 42 peptide., Methods: 5 Aβ 42 peptide represented as A, B, C, D and E were pretreated by HFIP. The pretreated Aβ 42 peptide were dissolved in Thioflavin T (ThT) solution, and their aggregation kinetics was monitored for 30 h with the aggregation kinetics test. Meanwhile, the pretreated peptide were aggregated in phosphate buffered saline. After aggregated for 12 h, they were detected by methods of ThT fluorescence, far-UV circular dichroism (CD), SDS-PAGE, western blot, and transmission electron microscopy (TEM), respectively. After aggregation for 8 h and 12 h, their cytotoxicity to SH-SY5Y cells was further evaluated using Cell Counting Kit-8., Results: For aggregation kinetics, peptide A, C and E remained low level curves, while peptide B and D presented typical sigmoidal kinetics curves. In CD measurement, the aggregates of peptide B and D showed relatively high negative CD peaks with the height of -8.09 mdeg and -14.37 mdeg, while the height of peptide A, C and E was -1.04, -3.55, and -3.88. In ThT assay, relative fluorescence intensity of the aggregates of peptide B and D were 7.79 and 8.82, higher than 1.19, 1.71, and 2.70 of peptide A, C and E, respectively. In SDS-PAGE, all aggregates contained monomers and eleven polymers. Moreover, peptide B-E presented a trapezoidal distribution from dimers to trimers, and peptide A aggregated to dimers. By western blot, the bands of monomers remained in all aggregates. Furthermore, peptide B and D aggregated to dimers and trimers, peptide A and C only aggregated to dimers, and peptide E showed a strong band of trimers. By TEM, protofibrils were observed only in peptide B, while substantial spherical aggregates were formed in other peptide. Additionally, peptide B, D and E exhibited higher cytotoxicity after aggregated for 8 h, whereas peptide A, B and D presented relatively high cytotoxicity after 12-hour aggregation., Conclusion: Commercially available Aβ 42 peptide showed obvious differences in aggregation ability, which should arouse enough attention in the field of basic study related to Aβ 42 . The aggregation ability evaluation with the various assay methods has some discrepancies, and it is highly urgent to establish a reasonable and uniform measurement strategy., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Cancer is one of the most dangerous diseases to human health. The accurate prediction of anticancer peptides (ACPs) would be valuable for the development and design of novel anticancer agents. Current deep neural network models have obtained state-of-the-art prediction accuracy for the ACP classification task. However, based on existing studies, it remains unclear which deep learning architecture achieves the best performance. Thus, in this study, we first present a systematic exploration of three important deep learning architectures: convolutional, recurrent, and convolutional-recurrent networks for distinguishing ACPs from non-ACPs. We find that the recurrent neural network with bidirectional long short-term memory cells is superior to other architectures. By utilizing the proposed model, we implement a sequence-based deep learning tool (DeepACP) to accurately predict the likelihood of a peptide exhibiting anticancer activity. The results indicate that DeepACP outperforms several existing methods and can be used as an effective tool for the prediction of anticancer peptides. Furthermore, we visualize and understand the deep learning model. We hope that our strategy can be extended to identify other types of peptides and may provide more assistance to the development of proteomics and new drugs., (© 2020 The Author(s).)

Background: Long noncoding RNAs have essential roles in human diseases, including cancer. Our work aims to assess the function and mechanisms of LINC01410 in cervical cancer (CC) development., Methods: Expression analyses were performed using qRT-PCR. Proliferation was determined through CCK8 and colony formation assays. Cell migration and invasion were determined by Transwell assay. The interactions among LINC01410, miR-2467-3p and VOPP1 were analyzed via luciferase reporter assay., Results: LINC01410 was upregulated in CC tissues and cell lines. LINC01410 upregulation correlated with poor prognosis. LINC01410 silencing suppressed proliferation, migration and invasion of CC cells. LINC01410 was the sponge for miR-2467. And LINC01410 promoted VOPP1 expression through inhibiting miR-2467., Conclusion: Our findings demonstrated that LINC01410 contributed to CC progression through regulating miR-2467/VOPP1 axis and suggested that LINC01410/miR-2467/VOPP1 cascade may be a potential therapeutic target., Competing Interests: Both authors declare no conflict of interest., (© 2020 Liu and Wen.)

Purpose: Individual lifespans vary widely, and longevity is the main concern from ancient to modern times. This study is aimed to identify plasma proteins associated with longevity by proteomics technique., Experimental Design: Tandem mass tags (TMT)-based proteomics analysis is performed for the plasma of Bama longevity group and a control group to analyze the differentially expressed proteins (DEPs). A validation set is used to verify the results of TMT-based proteomics., Results: Between Bama natives and the control individuals, the authors identify 175 DEPs, which are mainly involved in complement and coagulation cascades, metabolism of glyco and lipid, and regulation of actin cytoskeleton. Consistent with the proteomic analysis, plasma levels of MMP2, CCL5, and PF4 are significantly lower in Bama participants than in controls, whereas IGFBP2 and C9 increase in Bama individuals, in the validation set. By ROC analysis, combinations of these five proteins result in a high AUC value (0.991, 95% CI, 0.929-1.000, p < 0.0001) to distinguish longevous participants from controls., Conclusions and Clinical Relevance: The results highlight the roles of complement and coagulation cascades, metabolism of glyco and lipid, and inflammatory and immune response may play important roles in longevity. And the DEPs may serve as clinically useful biomarkers for healthy aging and predicting longevity., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

High-altitude polycythemia (HAPC) is one of the classic chronic mountain sicknesses and has been a serious public health problem in high-altitude regions. Despite numerous studies on HAPC via genomics or transcriptomics approaches, the pathogenesis of HAPC is still unclear. Here, we performed a TMT- based comparative quantitative proteomics analysis to reveal the changes of plasma proteomics profiles between HAPC subjects and healthy controls. Of identified 818 proteins, 7 and 12 proteins were up-regulated and down-accumulated, respectively, compared HAPC patients with healthy controls. GO and KEGG pathway analyses revealed the dysregulated proteins were primarily involved in complement and coagulation cascades, inflammation and immune response. ELISA validation demonstrated that C4A, C6 and CALR were down-regulated, and MASP1 and CNDP1 were up-regulated in HAPC patients. By ROC analysis, combinations of these five proteins (i.e., C4A, C6, CALR, MASP1 and CNDP1) resulted in a high AUC value (0.919; 95% CI, 0.817-961; p < .0001) to diagnose HAPC patients. Moreover, CNDP1 seems to be a robust biomarker for HAPC. This study not only provided a comprehensive dataset on overall proteomics changes in HAPC patients compared with healthy controls, but also indicated that CNDP1 can serve as a strong plasma biomarker of HAPC for the diagnostic and therapeutic potential. SIGNIFICANCE: HAPC, one of the classic chronic mountain sicknesses, has been a serious public health problem in high-altitude regions. Despite numerous studies on HAPC via genomics or transcriptomics approaches, the pathogenesis of HAPC is still largely unknown to date. In this study, we addressed this issue by performing TMT-based quantitative analyses of the plasma proteome profiles of HAPC patients and healthy controls. We identified 818 proteins, of which 19 were differentially expressed. Bioinformatics analysis revealed the differentially expressed proteins were mainly involved in complement and coagulation cascades, inflammation and immune response. By ROC analysis, combinations of C4A, C6, CALR, MASP1 and CNDP1 resulted in a high AUC value (0.919, p < .0001) to distinguish HAPC patients from healthy controls. Collectively, the current study provided a comprehensive dataset on overall proteomic changes in HAPC patients for the first time, and it also revealed C4A, C6, CALR, MASP1 and CNDP1 can be served as candidate plasma biomarkers of HAPC for their diagnostic and therapeutic potential., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Pig-to-human organ transplantation has drawn attention in recent years due to the potential use of pigs as an alternative source of human donor organs. While GGTA1 knockout (GTKO) can protect xenografts from hyperacute rejection, complement-dependent cytotoxicity might still contribute to this type of rejection. To prolong the xenograft survival, we utilized a T2A-mediated pCMV-hCD55-T2A-hCD59-Neo vector and transfected the plasmid into GTKO Diannan miniature pig fetal fibroblasts. After G418 selection combined with single-cell cloning culture, four colonies were obtained, and three of these were successfully transfected with the hCD55 and hCD59. One of the three colonies was selected as donor cells for somatic cell nuclear transfer (SCNT). Then, the reconstructed embryos were transferred into eight recipient gilts, resulting in four pregnancies. Three of the pregnant gilts delivered, yielding six piglets. Only one piglet carried hCD55 and hCD59 genetic modification. The expression levels of the GGTA1, hCD55, and hCD59 in the tissues and fibroblasts of the piglet were determined by q-PCR, fluorescence microscopy, immunohistochemical staining, and western blotting analyses. The results showed the absence of GGTA1 and the coexpression of the hCD55 and hCD59. However, the mRNA expression levels of hCD55 and hCD59 in the GTKO/hCD55/hCD59 pig fibroblasts were lower than that in human 293T cells, which may be caused by low copy number and/or CMV promoter methylation. Furthermore, we performed human complement-mediated cytolysis assays using human serum solutions from 0 to 60%. The result showed that the fibroblasts of this triple-gene modified piglet had greater survival rates than that of wild-type and GTKO controls. Taken together, these results indicate that T2A-mediated polycistronic vector system combined with SCNT can effectively generate multiplex genetically modified pigs, additional hCD55 and hCD59 expression on top of a GTKO genetic background markedly enhance the protective effect towards human serum-mediated cytolysis than those of GTKO alone. Thus, we suggest that GTKO/hCD55/hCD59 triple-gene-modified Diannan miniature pig will be a more eligible donor for xenotransplantation.

The IgG activities of antigen recognition, Fc-mediated complement activation and cellular Fcγ-receptors (FcγRs) binding are critical for intravenous immunoglobulin (IVIg) immunotherapy in a variety of immune deficiency diseases. Further, these activities could be influenced by different plasma sources and the IVIg manufacturing processes of different manufacturers. This study evaluated and compared the biological activities of IgG in 7 IVIg preparations produced by different Chinese manufacturers. By using ELISA and two-dimensional immunoblotting, the binding capacity and antibody repertoire of IVIg against typical pathogenic antigens were investigated. Further, Fc-mediated complement activation and receptor binding activities were measured by the haemolysis method and flow-cytometric assay respectively. The results showed that all of the preparations tested have a broad spectrum of antibodies against the E. coli O157:H7 proteome, and each IVIg has its own distinct antibody repertoire. Compared to the European Pharmacopoeia IgG standard, the mean indices of the pathogenic antigen binding capacity, complement activation activity and FcγRs binding activity in Chinese preparations were 152%, 143% and 87%. The biological activities varied widely among the 7 IVIg preparations, and no significant differences were observed between the different batches of most IVIgs from the same manufacturer. This study will contribute to the improvement of the IVIg product quality evaluation system and an increased understanding of the variety of IgG biological activities in Chinese IVIg preparations., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objective: To investigate the impact of a Croton tiglium extract on cellular proliferation and apoptosis in a nonsmall cell lung cancer cell line (A549) in vitro. Methods: A Croton tiglium seed methanol extract was prepare and assessed for effects on A549 cells regarding cellular proliferation, apoptotic rates, and expression of apoptosis related genes and proteins using real-time PCR and immunofluorescence. Results: The tested Croton tiglium extract inhibited A549 cell proliferation in a dose- and time-dependent manner, with significant elevation of apoptotic indexes at various concentrations after 24 h. In addition, rates in both early and late stages were higher in treated than untreated groups, the 100 μg/ml dose causing the highest levels of apoptosis. RT-PCR showed that A549 cells treated with 100 μg/ml Croton tiglium extract for 24 h has markedly higher Bax mRNA expression levels and obviously lower Bcl-2 expression levels than controls, equivalent results being observed for proteins by immunofluorescence. However, the mRNA expression levels of Fas and caspase-8 were not significantly altered. Conclusion: A Croton tiglium extract can inhibit proliferation of A549 cells and promote apoptosis though Bax/Bcl-2 pathways., (Creative Commons Attribution License)